Tag

#RAG

12 articles

RAG-Anything Tutorial: Build a Multimodal Retrieval Pipeline for Text, Tables, Equations, and Images in Colab

This article explains the RAG-Anything framework, a multimodal extension of Retrieval-Augmented Generation that retrieves and integrates information across text, tables, equations, and images.

Jul 225

Mistral OCR 4 Brings Citation-Ready Structured Output to RAG, Agentic, and Enterprise Search Pipelines

Mistral AI's Mistral OCR 4 introduces citation-ready, structured document outputs that enhance RAG, agentic, and enterprise search pipelines. The model supports 170 languages and runs in a single self-hosted container.

Jun 2334

tech

Crawlee for Python: Build a Web Crawling Pipeline with Robots Handling, Link Graphs, and RAG Chunk Export

Explore Crawlee for Python, a powerful web crawling framework designed for building scalable data pipelines that support AI applications like RAG. Learn how it handles JavaScript rendering, link graphs, and data export.

Jun 2037

tech

Google Cloud Introduces Open Knowledge Format (OKF): A Vendor-Neutral Markdown Spec for Giving AI Agents Curated Context

This explainer introduces the Open Knowledge Format (OKF), a vendor-neutral specification for structuring knowledge for AI agents. It explains how OKF uses Markdown and YAML to create curated knowledge bundles, distinguishing it from traditional RAG systems.

Jun 1542

tools

Meet Turbovec: A Rust Vector Index with Python Bindings, and Built on Google’s TurboQuant Algorithm

Turbovec, a new Rust-based vector index built on Google's TurboQuant algorithm, offers 16x compression and zero codebook training for RAG pipelines.

May 2048

tech

Best Vector Databases in 2026: Pricing, Scale Limits, and Architecture Tradeoffs Across Nine Leading Systems

Vector databases are becoming essential for RAG and agentic AI systems. A new analysis compares nine leading platforms on architecture, pricing, and scalability.

May 1037

RAG Without Vectors: How PageIndex Retrieves by Reasoning

Learn how PageIndex is revolutionizing information retrieval in AI by using reasoning instead of traditional vector-based methods, making AI systems smarter and more accurate.

Apr 2548

A Coding Implementation on Qwen 3.6-35B-A3B Covering Multimodal Inference, Thinking Control, Tool Calling, MoE Routing, RAG, and Session Persistence

This article explains the advanced AI concepts behind Qwen 3.6-35B-A3B, a multimodal model that combines MoE routing, RAG, and session persistence for intelligent, context-aware AI applications.

Apr 2066

A Coding Implementation on Microsoft’s Phi-4-Mini for Quantized Inference Reasoning Tool Use RAG and LoRA Fine-Tuning

This article explains how Microsoft's Phi-4-Mini AI model uses quantization, RAG, and LoRA techniques to create efficient, powerful language models that can answer questions and use tools.

Apr 2053

Salesforce AI Research Releases VoiceAgentRAG: A Dual-Agent Memory Router that Cuts Voice RAG Retrieval Latency by 316x

Salesforce AI Research introduces VoiceAgentRAG, a dual-agent memory router that cuts voice RAG retrieval latency by 316 times, enhancing conversational AI responsiveness.

Mar 3091

Google AI Introduces Gemini Embedding 2: A Multimodal Embedding Model that Lets Your Bring Text, Images, Video, Audio, and Docs into the Embedding Space

Learn to implement multimodal embeddings using Google's Gemini Embedding 2 model for cross-modal retrieval and RAG applications.

Mar 10108

VectifyAI Launches Mafin 2.5 and PageIndex: Achieving 98.7% Financial RAG Accuracy with a New Open-Source Vectorless Tree Indexing.

VectifyAI launches Mafin 2.5 and PageIndex, achieving 98.7% financial RAG accuracy with a new vectorless tree indexing approach.

Feb 23108